The A2iA Arabic Handwritten Text Recognition System at the Open HaRT2013 Evaluation
Théodore Bluche, Jérôme Louradour, Maxime Knibbe, Bastien Moysset, Mohamed Faouzi BenZeghiba, Christopher Kermorvant · 2014
This paper describes the Arabic handwriting recognition systems proposed by A2iA to the NIST OpenHaRT2013 evaluation. These systems were based on an optical model using Long Short-Term Memory (LSTM) recurrent neural networks, trained to recognize the different forms of the Arabic characters directly from the image, without explicit feature extraction nor segmentation.Large vocabulary selection techniques and n-gram language modeling were used to provide a full paragraph recognition, without explicit word segmentation. Several recognition systems were also combined with the ROVER combination algorithm. The best system exceeded 80% of recognition rate.